Visualization of Lidar-Based 3D Droplet Distribution Detection for Air-Assisted Spraying

Author:

Wang Zhichong12ORCID,Zhang Yang1,Li Tian234,Müller Joachim1ORCID,He Xiongkui234ORCID

Affiliation:

1. Tropics and Subtropics Group, Institute of Agricultural Engineering, University of Hohenheim, 70599 Stuttgart, Germany

2. College of Agricultural Unmanned System, China Agricultural University, Beijing 100193, China

3. College of Science, China Agricultural University, Beijing 100193, China

4. Centre for Chemicals Application Technology, China Agricultural University, Beijing 100193, China

Abstract

Air-assisted spraying is a commonly used spraying method for orchard plant protection operations. However, its spraying parameters have complex effects on droplet distribution. The lack of large-scale 3D droplet density distribution measurement methods of equipment has limited the optimization of spraying parameters. Therefore, there is a need to develop a method that can quickly obtain 3D droplet distribution. In this study, a 2D LiDAR was used to quickly scan moving droplets in the air, and a test method that can obtain the visualization of 3D droplet distribution was constructed by using the traveling mode of the machine perpendicular to the scanning plane. The 3D droplet distribution at different positions of the nozzle installed in the air-assisted system was tested at different fan rotation speeds, and the methods for signal processing, point cloud noise reduction, and point cloud division for 2D LiDAR were developed. The results showed that the LiDAR-based method for detecting 3D droplet distribution is feasible, fast, and environmentally friendly.

Funder

2115 Talent Development Program of China Agricultural University, Sanya Institute of China Agricultural University Guiding Fund Project

earmarked fund for CARS

Publisher

MDPI AG

Subject

Engineering (miscellaneous),Horticulture,Food Science,Agronomy and Crop Science

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